Pheromone Robotics

All about Pheromone Robots and Robot Swarms

Overview

The Pheromone Robotics project aims to
provide a robust, scalable approach for coordinating actions of large numbers
of small-scale robots to achieve large scale results in surveillance,
reconnaissance, hazard detection, path finding, payload conveyance, and
small-scale actuation. We intend to accomplish this by developing innovative
concepts for coordinating, and interacting with, a large collective of tiny
robots. Borrowing techniques used by certain insects, e.g. ants and termites,
our robots exhibit emergent collaboration. Inspired by the chemical markers
used by these insects for communication and coordination, we exploit the notion
of a "virtual pheromone," implemented using simple beacons and
directional sensors mounted on each robot. Virtual pheromones facilitate simple
communication and coordination and require little on-board processing. Our
approach is applicable to future robots with much smaller form factors (e.g.,
to dust-particle size) and is scaleable to large, heterogeneous groups of
robots.

We provide robustness by requiring no explicit
maps or models of the environment, and no explicit knowledge of robot location.
Collections of robots will be able to perform complex tasks such as leading the
way through a building to a hidden intruder or locating critical choke points.
This is possible because the robot collective becomes a computing grid embedded
within the environment while acting as a physical embodiment of the user
interface. Over the past decades, the literature on path planning and terrain
analysis has dealt primarily with algorithms operating on an internal map
containing terrain features. Our approach externalizes the map, spreading it
across a collection of simple processors, each of which determines the terrain
features in its locality. The terrain processing algorithms of interest are
then spread over the population of simple processors, allowing such global
quantities as shortest routes, blocked routes, and contingency plans to be
computed by the population.

The user interface to this distributed robot
collective is itself distributed. Instead of communicating with each robot
individually, the entire collective will work cooperatively to provide a
unified display embedded in the environment. For example, robots that have
dispersed themselves throughout a building will be able to guide a user toward
an intruder by synchronizing to collectively blink in a marquee-style pattern
to highlight the shortest path to the intruder. Through the use of augmented
reality, robots are able to present more complex displays. For example, users
wearing a see-through head-mounted display and a head-mounted camera that
detects and tracks infrared beacons emanating from the robots are able to see a
small amount of information superimposed over each robot. Each robot, in
effect, becomes a pixel that paints information upon its local environment. The
combination of this world-embedded interface with our world-embedded
computation means that the results of complex distributed computations can be
mapped directly onto the world with no intermediate representations required.